Covariance for joint distribution
cov_joint(cov)cov_par(cov, horizon = 1, n_var, joint = FALSE)
The joint covariance matrix for the joint distribution of the current values and the past values for a Markov chain Gaussian field.
Array of covariance matrices.
Forecast horizon, default is 1.
Number of locations.
Logical; True if cov is the joint covariance matrix.
The covariance matrix of the joint distribution has the block toeplitz
structure. Input cov is assumed to be an array of cross-covariance matrices
where the \(i\)th matrix slice correspond to the \((i-1)\)th time lag.
For example, cov[, , 1] is the cross-covariance matrix for time lag 0. All
matrices in cov are used to construct the joint covariance matrix.
cov_par gives weights and covariance matrix for the current values..